Comparative physiogenomic analyses of weight loss in response to 2 modes of bariatric surgery: demonstration with candidate neuropsychiatric and cardiometabolic genes.

ABSTRACT

BACKGROUND: Surgical weight loss response is variable, with suboptimal outcomes in some patients. We hypothesized that genetic biomarkers may be related to weight change. METHODS: We tested 330 single nucleotide polymorphisms (SNPs) in genes relevant to metabolic regulation in 161 patients whose decrease in body mass index (BMI), 1 year after laparoscopic adjustable gastric banding (LAGB) or Roux-en-Y gastric bypass (RYGB), was small (lowest quartile response) or large (highest quartile response). LAGB patients whose BMI decreased≤4.7 or≥10.2 units comprised groups I (n = 43) and II (n = 40), respectively. RYGB patients whose BMI decreased≤13.6 or≥19.8 units comprised groups III (n = 39) and IV (n = 39), respectively. Within each surgery, SNPs with large differences in reference allele frequency (z score>2, corresponding to values displaced 2 standard deviations [SD] from the mean for all SNPs) in low versus high quartiles, were identified. We compared reference allele frequencies, within surgical procedure, using the χ(2) test (using Bonferroni correction for multiple testing). RESULTS: The mean percent excess weight losses (±SD) corresponding to groups I, II, III, and IV were 16 (±12), 64 (±30), 55 (±16), and 75 (±17), respectively. SNPs with z score>2 were identified in genes involved in LAGB response, lipid metabolic regulation (APOE, rs439401; APOC4, rs2288911), neural processes (DRD3, rs167771; HTR3 B, rs3758987), and xeno- or endobiotic metabolism (CYP3 A4, rs12333983); and for RYGB response, in lipid transport (SCARB1, rs10846744), folate metabolism (MTHFR, rs2066470), regulation of glycolysis in immune cells (HIF1 A, rs1951795), vitamin K cycling (VKORC1, rs2359612), and xeno- or endobiotic metabolism (CYP3 A4, rs2242480). For LAGB response, APOE SNP frequencies were significantly different. CONCLUSIONS: With further validation, information derived from patient DNA may be useful to predict surgical weight loss outcomes and guide selection of surgical approach.